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mgartner/pg_flame

A flamegraph generator for Postgres EXPLAIN ANALYZE output. observed · 2026-08-28

github.com/mgartner/pg_flame · Go · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

23/100

  • Activity 0
  • Release rhythm 8
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 2513
  • days_rel: n/a
  • days_push: 2424
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1620 stars · 36 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

pg_flame is a command-line tool that converts Postgres EXPLAIN ANALYZE JSON output into an interactive flamegraph HTML visualization. It helps developers see where time is spent in query plan execution.

Use cases

  • visualize postgres query plan execution times as a flamegraph
  • debug slow postgres queries
  • turn EXPLAIN ANALYZE JSON output into a flamegraph
  • find which parts of a query plan consume the most time
  • profile postgres query performance

When to choose

  • you want a quick, pipeable CLI to visualize Postgres EXPLAIN ANALYZE output
  • you prefer simple stdin/stdout Unix-style tooling
  • you need a lightweight alternative to full query analyzers

When to avoid

  • you need a GUI query analyzer with historical tracking
  • you use databases other than Postgres
  • you need actively developed features or support

Facets

cli-tool · maturity maintenance

data-visualization developer-tools databases performance developer-tools cli windows flamegraph postgresql explain-analyze query-plans go linux macos docker

1 source

Member repositories

RepositoryRoleHealth v2
mgartner/pg_flamemain23

For agents

markdown · JSON · MCP: product_card(name="mgartner/pg_flame")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem